Man-Lai Tang
Biographic Data
| ID | 4270794 |
|---|---|
| NAME | Man-Lai Tang |
| GIVEN NAMES | Man-Lai |
| FAMILY NAME | Tang |
| SIGNATURE | TANG M |
| AFFILIATIONS | Harvard University |
| VERIFIED | No |
| TOTAL WORKS | 5 |
| TOTAL CITATIONS | 0 |
| WORKS AS AUTHOR | 5 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 1998 |
| LATEST PUBLICATION YEAR | 2021 |
| H-INDEX | 0 |
Analysis of the Spread of Covid-19 in the USA with a Spatio-Temporal Multivariate Time Series Model
With the rapid spread of the pandemic due to the coronavirus disease 2019 (COVID-19), the virus has already led to considerable mortality and morbidity worldwide, as well as having a severe impact on economic development. In this article, we analyze the state-level correlation between COVID-19 risk and weather/climate factors in the USA. For this purpose, we consider a spatio-temporal multivariate time series model under a hierarchical framework,…
Incomplete Categorical Data Design
Respondents to survey questions involving sensitive information, such as sexual behavior, illegal drug usage, tax evasion, and income, may refuse to answer the questions or provide untruthful answers to protect their privacy. This creates a challenge in drawing valid inferences from potentially inaccurate data. Addressing this difficulty, non-rando
Constrained Maximum Likelihood Estimation for Two-Level Mean and Covariance Structure Models
Maximum likelihood is commonly used for the estimation of model parameters in the analysis of two-level structural equation models. Constraints on model parameters could be encountered in some situations such as equal factor loadings for different factors. Linear constraints are the most common ones and they are relatively easy to handle in maximum likelihood analysis. Nonlinear constraints could be encountered in complicated applications. The au…
Influence Measures in Contingency Tables With Application in Sampling Zeros
Based on the local influence approach with an appropriate perturbation scheme, measures are developed to assess the influence of an individual cell in contingency tables. The authors demonstrate that the developed measures are particularly suitable for sensitivity analysis in tables with sampling zeros. The independence model and the log-linear model, together with numerical examples, are presented for illustration
Tests of Independence for Ordinal Data Using Bootstrap
In a two-way cross table, the association between two ordinal variables can be assessed by different measures such as Goodman and Kruskal's gamma (y) and Kendall's tau-b (tb). When sample size is large, the independence hypothesis between the row and the column variables can be tested by the traditional asymptotic test (TAT). TAT, however, fails to work satisfactorily when sample size is small because the theoretical distribution of the test stat…
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Tests of Independence for Ordinal Data Using Bootstrap
In a two-way cross table, the association between two ordinal variables can be assessed by different measures such as Goodman and Kruskal's gamma (y) and Kendall's tau-b (tb). When sample size is large, the independence hypothesis between the row and the column variables can be tested by the traditional asymptotic test (TAT). TAT, however, fails to work satisfactorily when sample size is small because the theoretical distribution of the test stat…
Influence Measures in Contingency Tables With Application in Sampling Zeros
Based on the local influence approach with an appropriate perturbation scheme, measures are developed to assess the influence of an individual cell in contingency tables. The authors demonstrate that the developed measures are particularly suitable for sensitivity analysis in tables with sampling zeros. The independence model and the log-linear model, together with numerical examples, are presented for illustration
Constrained Maximum Likelihood Estimation for Two-Level Mean and Covariance Structure Models
Maximum likelihood is commonly used for the estimation of model parameters in the analysis of two-level structural equation models. Constraints on model parameters could be encountered in some situations such as equal factor loadings for different factors. Linear constraints are the most common ones and they are relatively easy to handle in maximum likelihood analysis. Nonlinear constraints could be encountered in complicated applications. The au…
Incomplete Categorical Data Design
Respondents to survey questions involving sensitive information, such as sexual behavior, illegal drug usage, tax evasion, and income, may refuse to answer the questions or provide untruthful answers to protect their privacy. This creates a challenge in drawing valid inferences from potentially inaccurate data. Addressing this difficulty, non-rando
Analysis of the Spread of Covid-19 in the USA with a Spatio-Temporal Multivariate Time Series Model
With the rapid spread of the pandemic due to the coronavirus disease 2019 (COVID-19), the virus has already led to considerable mortality and morbidity worldwide, as well as having a severe impact on economic development. In this article, we analyze the state-level correlation between COVID-19 risk and weather/climate factors in the USA. For this purpose, we consider a spatio-temporal multivariate time series model under a hierarchical framework,…
Computer Science (4 works) · Econometrics (4 works) · Mathematics (4 works) · Statistics (4 works) · Statistical Methods and Inference (3 works) · Advanced Statistical Methods and Models (2 works) · Contingency table (2 works) · Independence (probability theory) (2 works) · Statistical Methods and Bayesian Inference (2 works) · Analysis of covariance (1 work)